Home

Awesome

<a href="https://github.com/nteract/papermill"><img src="https://media.githubusercontent.com/media/nteract/logos/master/nteract_papermill/exports/images/png/papermill_logo_wide.png" height="48px" /></a>

<!---(binder links generated at https://mybinder.readthedocs.io/en/latest/howto/badges.html and compressed at https://tinyurl.com) -->

Travis Build Status Azure Build Status image Documentation Status badge badge Code style: black

papermill for CI/CD is a tool for parameterizing, executing, and analyzing Jupyter Notebooks.

Papermill lets you:

This opens up new opportunities for how notebooks can be used. For example:

Modifications to original library

Installation

From the command line:

pip install papermill

For all optional io dependencies, you can specify individual bundles like s3, or azure -- or use all

pip install papermill[all]

Python Version Support

This library will support python 2.7 and 3.5+ until end-of-life for python 2 in 2020. After which python 2 support will halt and only 3.x version will be maintained.

Usage

Parameterizing a Notebook

To parameterize your notebook designate a cell with the tag parameters.

enable parameters in Jupyter

Papermill looks for the parameters cell and treats this cell as defaults for the parameters passed in at execution time. Papermill will add a new cell tagged with injected-parameters with input parameters in order to overwrite the values in parameters. If no cell is tagged with parameters the injected cell will be inserted at the top of the notebook.

Additionally, if you rerun notebooks through papermill and it will reuse the injected-parameters cell from the prior run. In this case Papermill will replace the old injected-parameters cell with the new run's inputs.

image

Executing a Notebook

The two ways to execute the notebook with parameters are: (1) through the Python API and (2) through the command line interface.

Execute via the Python API

import papermill as pm

pm.execute_notebook(
   'path/to/input.ipynb',
   'path/to/output.ipynb',
   parameters = dict(alpha=0.6, ratio=0.1)
)

Execute via CLI

Here's an example of a local notebook being executed and output to an Amazon S3 account:

$ papermill local/input.ipynb s3://bkt/output.ipynb -p alpha 0.6 -p l1_ratio 0.1

NOTE: If you use multiple AWS accounts, and you have properly configured your AWS credentials, then you can specify which account to use by setting the AWS_PROFILE environment variable at the command-line. For example:

$ AWS_PROFILE=dev_account papermill local/input.ipynb s3://bkt/output.ipynb -p alpha 0.6 -p l1_ratio 0.1

In the above example, two parameters are set: alpha and l1_ratio using -p (--parameters also works). Parameter values that look like booleans or numbers will be interpreted as such. Here are the different ways users may set parameters:

$ papermill local/input.ipynb s3://bkt/output.ipynb -r version 1.0

Using -r or --parameters_raw, users can set parameters one by one. However, unlike -p, the parameter will remain a string, even if it may be interpreted as a number or boolean.

$ papermill local/input.ipynb s3://bkt/output.ipynb -f parameters.yaml

Using -f or --parameters_file, users can provide a YAML file from which parameter values should be read.

$ papermill local/input.ipynb s3://bkt/output.ipynb -y "
alpha: 0.6
l1_ratio: 0.1"

Using -y or --parameters_yaml, users can directly provide a YAML string containing parameter values.

$ papermill local/input.ipynb s3://bkt/output.ipynb -b YWxwaGE6IDAuNgpsMV9yYXRpbzogMC4xCg==

Using -b or --parameters_base64, users can provide a YAML string, base64-encoded, containing parameter values.

When using YAML to pass arguments, through -y, -b or -f, parameter values can be arrays or dictionaries:

$ papermill local/input.ipynb s3://bkt/output.ipynb -y "
x:
    - 0.0
    - 1.0
    - 2.0
    - 3.0
linear_function:
    slope: 3.0
    intercept: 1.0"

Supported Name Handlers

Papermill supports the following name handlers for input and output paths during execution:

Development Guide

Read CONTRIBUTING.md for guidelines on how to setup a local development environment and make code changes back to Papermill.

For development guidelines look in the DEVELOPMENT_GUIDE.md file. This should inform you on how to make particular additions to the code base.

Documentation

We host the Papermill documentation on ReadTheDocs.